『The Cyber Risk Discourse is Broken』のカバーアート

The Cyber Risk Discourse is Broken

The Cyber Risk Discourse is Broken

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10月19日まで。※適用条件あり
I’ve had one too many discussions on the cyber risks of open models — where someone assumes that either banning open models happens in a silo (and bad actors will somehow actually be stopped) or that China is a threat and doesn’t care about AI safety — that I feel we’re going to end up making policy decisions that both limit American AI competitiveness and increases long-term cyber risk. I feel like we’re locked in on a path of lose-lose situation, unless people embrace nuance, trade-offs, and scary realities.Much has been written about the views of various players in this debate, which I summarize as follows:* Open weight models pose an untenable risk to society’s functionality, occupied by frontier lab leadership and the national security community in the U.S.* Western voices saying open weight models are necessary for defense and banning them will make the world less safe, occupied by AI risk moderates to different extremes. I include myself in this bucket, along with Hugging Face’s perspective after the OpenAI incident, and others like Joshua Saxe.* Chinese companies continuing to release open-weight models with strong cyber capabilities, who are making decisions based on the risk assessments of their society and government.This list is also organized by volume or clarity of message in the Western AI ecosystem. The risk-focused discussions have been disproportionately visible, including pieces of work which I view as very detrimental to potential of engaging across assumed party lines on this issue. There’s also very little substantive engagement trying to understand how Chinese companies assess risk — rather, mostly arguments that border on ad hominem attacks like “Chinese labs don’t care about safety.” Interconnects AI is a reader-supported publication. Consider becoming a subscriber.The delusions of the anti open-weight allianceThe most recent publication from the “open-weights are dangerous” crowd was the report by Anthropic on the risks of GLM-5.3 as an offensive cyber tool. The problem with this is not the technical research they did, which is largely reasonable, but the failure to engage on more cross cutting questions like: What happens if we ban open models due to cyber risks or why do Chinese companies deem these models safe to release?These questions, which I’ll come back to, are the ones we need to answer to understand the ecosystem perspective on current AI risks. All policy actions happen in a multi-piece puzzle, where the shape of risk can be changed, but it is rare that you get a universally better outcome. They are all trade-offs.This sort of solipsistic writing by Anthropic fits very closely to another type of discourse I’m hearing about regularly that is determining the fate of open models and AI broadly — classified briefings. I’ve had many discussions with people who say something like “Look, I’m pro open models, but if you’re seeing what I’m seeing, it’s an onslaught out there due to [XYZ Chinese open-weight model] and we need to act.” This perspective flies in the face of public information, where to date closed models have been documented as the cause of most existing cyber attacks. As someone who tries to make grounded predictions, the evidence of numerous attacks from OpenAI models is the only data I have on the shape of cyber risks (or, you can broaden the scope to include all of FelonyBench). There are a few possible explanations, and it’ll take years to get to the true answer: * Maybe open model weights and closed model APIs (with some safe guards) are both far closer to being easy to mis-use, rather than API models being closer to safe. The trope "Open Dangerous, Closed Safe" may be closer to "Open Unsafe, Closed Unsafe."* Maybe there are far fewer bad actors who are willing to use AI models for “loud” cyber attacks that target crucial infrastructure in the US or powerful and underprepared institutions. Closed models have stronger capabilities and stronger safeguards (in theory), but the stronger capabilities part could matter more in net harm if the safeguards on both are porous. * I have a lot more to learn about how the cybersecurity ecosystem works, so I won’t support this full-heartedly as one of my current recommendations, but I think it’s at least a reasonable argument that open weight models as a diffusion tool for cyber defense could be the best tool we have to prevent harm over the next few years. There are many domains, e.g. sensitive government agencies, where open-weight models are the only tools that can be deployed in the near-term on air-gapped networks.Lots of this situation seems like the messy reality being hard to pin down, where the logical limits are clearer. I may agree with the simple reality that closed models are far safer in the limit, as a technical tool with more layers of protection, but they may actually be causing more harm in the near term because of how accessible model APIs ...
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